113 citations · 221 across the 19 of their papers we have counts for
4 papers · 1 filter
Estimating Information Flow in Deep Neural Networks
Ziv Goldfeld, Ewout van den Berg, Kristjan Greenewald +4
We study the flow of information and the evolution of internal representations during deep neural network (DNN) training, aiming to demystify the compression aspect of the informat…
Fighting Offensive Language on Social Media with Unsupervised Text Style Transfer
Cicero Nogueira dos Santos, Igor Melnyk, Inkit Padhi
We introduce a new approach to tackle the problem of offensive language in online social media. Our approach uses unsupervised text style transfer to translate offensive sentences…
Adversarial Semantic Alignment for Improved Image Captions
Pierre L. Dognin, Igor Melnyk, Youssef Mroueh +2
In this paper we study image captioning as a conditional GAN training, proposing both a context-aware LSTM captioner and co-attentive discriminator, which enforces semantic alignme…
Deep learning algorithm for data-driven simulation of noisy dynamical system
Kyongmin Yeo, Igor Melnyk
We present a deep learning model, DE-LSTM, for the simulation of a stochastic process with an underlying nonlinear dynamics. The deep learning model aims to approximate the probabi…